Biochar's dual impact on soil acidity management and crop yield enhancement: a meta-analysis

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Quantitative analysis of the impact of biochar application on soil pH and crop yield can help promote its optimal utilization. Methods We compiled 654 observations from 105 peer-reviewed articles to investigate the impact of biochar application on crop yield, soil pH and other physicochemical properties in acidic soils. Results Application of biochar significantly increased soil pH and crop yield by 11% and 49%, respectively. The increase in soil pH exhibited a positive correlation with crop yield, and the relationship varied among crop type. The most significant increase in soil pH and crop yield following biochar application was observed in strongly acidic soils (pH < 4.5) characterized by low cation exchange capacity, ranging from 5 to 10 cmol kg − 1 , and low soil organic matter content, < 6 g kg − 1 . Among soil physicochemical properties, biochar application increased soil organic matter, cation exchange capacity, and cation saturation by 54%, 33% and 43%, respectively, while reduced soil bulk density by 11%. Biochar derived from herbaceous sources and pyrolyzed at an optimal temperature of 300–400°C had a significant and positive affect on soil pH (+ 16%) and crop yield (+ 71%). Conclusion Our findings can aid in optimizing management strategies for biochar application on acidic soils, whereas more long-term field experiments should be conducted to help provide better explanations for changes in biochar properties as it ages. Biochar Crop yield Meta-analysis Soil acidification Soil properties Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Anthropogenic processes, such as agricultural practices, expedite soil acidification when compared with the natural soil development process (Guo et al. 2010 ; Bolan et al. 2023 ). Approximately 50% of all global arable land exhibits an acidic profile, and the percentage is gradually increasing due to on-going soil acidification (Kochian et al. 2015 ). Soil acidification has obtained significant attention due to its adverse effects on agriculture production and ecosystem services (Guo et al. 2010 ; Raza et al. 2020 ; Dai et al. 2017 ). It can facilitate the loss of cations (e.g., Na + , K + , Ca 2+ , Mg 2+ ), thus leading to a decline of soil fertility (Zhang et al. 2016 ). Acidification can also increase the solubility and mobility of toxic metal (e.g., Cd, Pb), making them more susceptible for crop uptake and increasing their potential to enter the food chain, thereby posing risks to the health of farm animals and humans (Zhu et al. 2018 ; Bolan et al. 2023 ). Additionally, the availability of aluminum (Al) and manganese (Mn) increases in the soil solution at low soil pH, resulting in root damage and decreased crop yield (Yadav et al. 2020 ). Those impacts can subsequently threaten food security, underscoring the urgent need to mitigate soil acidification to meet the increasing demand for food (Zhang et al. 2022 ). Various materials, including agriculture lime, biochar, manure, straw and sludge, are commonly used to relieve soil acidification in agricultural systems (Kätterer et al. 2019 ), among which biochar has been recognized as a promising amendment to overcome soil acidity (Masud et al. 2020 ; Hass et al. 2012 ; Mukherjee and Zimmerman 2013 ). Biochar is a carbon-rich solid product produced by pyrolysis of different kinds of biomass under oxygen-limited conditions (Yuan et al. 2021 ). Biochar can alleviate soil acidification in a direct way through thereaction of carbonates and oxides in biochar with the H + and monomeric Al to decrease soil exchangeable acidity, or in an indirect way by increasing NH 4 + -N sorption and thus decreasing nitrification rate to prevent H + production (Dai et al. 2017 ; Novak et al. 2009 ; Yang et al. 2015 ). The feedstock types and pyrolysis conditions together determine the biochar physicochemical properties, including pH, cation exchange capacity, and surface area (Pariyar et al. 2020 ; Mukherjee and Zimmerman 2013 ). Thereafter, it can further influence the potential to alleviate soil acidity (Mukherjee and Zimmerman 2013 ; Bolan et al. 2023 ). Biochar can be produced from a wide range of feedstock, including organic and industrial wastes (e.g., manure, sludge), plant-based materials (e.g., leaves, straw, husks, cobs), and wood-based products (e.g., woodchips, wood pellets) at different pyrolysis temperature under oxygen-limited condition (Farhangi-Abriz et al. 2021 ; Singh et al. 2022 ). Biochar pH varies from ~ 3.5 to ~ 12.2, and a higher pH does not necessarily relate to a greater capacity to increase soil pH. Papermill residue pyrolyzed at 550°C has a pH of 6.8 with an 18% acid-neutralizing capacity that of calcium carbonate, while biosolid-made biochar has a higher pH of 7.9 but with a 1.7% acid neutralizing capacity (van Zwieten et al. 2010b ). Meanwhile, the pH of green-waste at 350°C and 550°C pyrolysis temperature is 4.9 and 7.3, while the corresponding acid neutralizing capacity is 8.4% and 7.5%, respectively. Biochar application can ultimately increase crop yield (Arif et al. 2017 ; Biederman and Harpole 2013 ) due to increases in soil pH (Sun et al. 2017 ; Li et al. 2019b ; Bolan et al. 2023 ), soil carbon storage (Obia et al. 2016 ), and water and nutrient retention (Fischer et al. 2019 ; Bolan et al. 2023 ). However, it can also cause the decline of crop yield due to nutrient imbalances and enhanced adsorption of NO 3 − and NH 4 + , increased N immobilization, as well as slower N cycling (Borchard et al. 2014 ; Wei et al. 2020 ). Bass et al. ( 2016 ) reported that banana ( Musa sp.) crop yield decreases by 18% with biochar application, with no significant effect on papaya ( Carica papaya ) crop yield. Those contradictory results are usually attributed to the heterogeneity of soil type, properties of biochar as a function of feedstock types and pyrolysis conditions and experimental types (laboratory vs. pot vs. field) (Singh et al. 2022 ; Dai et al. 2017 ). A general conclusion on the influence of biochar application requires collecting all available data, to analyze the average effect size and the reasons for differences among studies. Meta-analysis is a comprehensive method to investigate studies with inconsistent results and explain differences among studies (Gurevitch et al. 2001 ). Thus, this study aim to conduct a meta-analysis to 1) quantify the effects of biochar application on soil pH, crop yield and soil physicochemical properties in acidic soils; 2) establish correlations between crop yield and soil properties. Materials and methods Data collection Literature published before July 2023 was collected from Web of Science and China National Knowledge Infrastructure (CNKI) using keywords: 'biochar', 'yield', 'acidic soil' in the topic field. A total of 272 articles were identified and screened based on the following specific criteria for inclusion in the meta-analysis. These criteria included: 1) the presence of a control without biochar application, with all other agronomic practices unchanged; 2) a minimum of three replicates for each treatment; 3) clear reporting of biochar materials and application rates; 4) inclusion of at least one of the following variables impacted by biochar: soil pH, crop yield, cation exchange capacity (CEC), organic matter (OM), bulk density (BD) and cation saturation (CS); 5) initial soil pH should be lower than 6.5, to exclude calcareous soils from the analysis; and 6) reporting of means, standard deviation (SD) or standard error (SE). When SD was unavailable, it was calculated by multiplying SE with the square root of the number of replicates. The GetData Graph Digitizer software was used to extract data from figures where numerical data were not explicitly presented. Finally, 105 peer-reviewed articles with 654 observations from 41 countries or regions were included to elucidate the impacts of biochar on soil pH and crop yield (Fig. 1 ). The screening process is shown in Fig. S1 . The extracted data were collated as the mean of control and biochar treatment, and corresponding standard deviation and sample size. The biochar characteristics, soil properties, and experimental conditions as provided in each article were also extracted as: 1) biochar characteristics: pH, pyrolysis temperature and feedstock type; 2) soil properties: pH, organic matter (OM), cation exchange capacity (CEC), bulk density (BD) and cation saturation (CS); 2) type of study: field, pot, incubation. Data categories Explanatory variables including crop, biochar feedstock type, biochar pH, pyrolysis temperature, soil OM, soil CEC, soil BD and soil CS and type of study were selected to explain the response variables (soil pH and crop yield). Each explanatory variable was classified as follows: Crop: maize, wheat, rice, legume (soybean, peanut, mung bean), vegetable (tomato, pepper, Chinese cabbage, lettuce, carrot etc.), grass, millet, fruit (citrus, papaya), tea and others; Biochar pH (BC pH): (1) BC pH ≤ 6.5, (2) 6.5 < BC pH ≤ 7.5, (3) 7.5 9.5, classified following Cayuela et al. ( 2014 ); Biochar feedstock type: (1) wood (hardwood, bamboo, oak, pine, etc.), (2) herbaceous (wheat straw, maize straw, rice straw, peanut shell, etc.), (3) biosolid (sludge, manure) (Jeffery et al. 2016 ); Biochar pyrolysis temperature (BC PT, ℃): (1) BC PT ≤ 300, (2) 300 < BC PT ≤ 400, (3) 400 500 (Yuan et al. 2021 ); Initial soil pH: (1) soil pH < 4.5, (2) 4.5 < soil pH < 5.0, (3) 5.0 < soil pH < 5.5, (4) 5.5 < soil pH < 6.0, (5) 6.0 < soil pH < 6.5 (Zhang et al. 2023 ); Soil CEC (cmol kg -1 ): (1) CEC ≤ 5, (2) 5 < CEC ≤ 10, (3) 10 20; Soil OM (g kg -1 ): (1) OM ≤ 6, (2) 6 < OM ≤ 12, (3) 12 20. Meta-analysis The natural log-transformed response ratio (RR) reflects the relative change in one of the response variables due to biochar application, and is calculated based on the ratio of treatment value and control value (Hedges et al. 1999 ): $$\text{ln}RR=\text{l}\text{n}\left(\frac{Xt}{Xc}\right)$$ where X t and X c represent the values of crop yield, soil pH, OM, CEC, CS and BD in treatment group with biochar application and control group without biochar application, respectively. Effect size was converted to % change according to the following equation (Nguyen et al. 2017 ): % change = ( \({e}^{\text{l}\text{n}\left(RR\right)}\) -1) × 100 Statistical analyses A mixed-effects model was selected to calculate effect size and 95% confidence intervals (CIs) for each categorical group using the R package 'metafor'. Significance in difference between biochar application and no biochar application was considered when the CIs did not overlap with zero (Hedges et al. 1999 ). Spearman correlations were conducted to examine the correlation between the effect sizes for soil pH, yield, CEC, OM, CS and BD with the cor.test function in R package of 'stats' (Suhadolnik et al. 2021 ). Egger’s test and Fail-safe number were applied to test the publication bias and robustness of the meta-analysis. The Fail-safe number was calculated and compared with 5n + 1 (n is the number of studies) when the Egger’s test was significant ( P < 0.05) (Rothstein et al. 2005 ). A boosted regression tree (BRT) analysis was performed to rank the relative influence of explanatory variables and thus address non-linearity and variable interactions (Elith et al. 2008 ). The mixed-effect model combined with BRT has been widely used in a number of meta-analyses (Nguyen et al. 2016 ; Nguyen et al. 2017 ; Yuan et al. 2021 ). R package 'gbm' was used to conduct the BRT analysis. A Gaussian error structure was used to estimate the optimal number of trees during a 10-fold cross validation, and the model parameters were as follows: tree complexity 5, learning rate 0.005 and bagging fraction 0.75. Results General trend Our meta-analysis demonstrates that overall, biochar application has a significant impact on soil pH and crop yield. The result of the BRT analysis shows the relative influence of explanatory variables, among which the pyrolysis temperature explains 43% of the change in soil pH, followed by soil CEC (20%), feedstock type (14%), type of study (13%) and soil OM (10%) (Fig. 2 ). For the change in crop yield, pyrolysis temperature explains the majority of the variation (54%), followed by type of study (31%), feedstock type (7%), soil OM (5%) and soil CEC (3%). Between-study heterogeneity was detected in the analyses of this meta-analysis. This was inevitable because the data in this meta-analysis were from a variety of experimental designs, experiment types, biochar characteristics, soil properties and crop types. A significant publication bias was identified ( P < 0.05) in the meta-analysis, while it did not affect the robustness of the meta-analysis according to the test of Fail-safe number (Table 1 ) (Nguyen et al. 2017 ; Yuan et al. 2021 ). Table 1 Test results of publication bias. Variables Egger's test ( P ) n a 5 n + 10 N fs b Is there a bias? Is the analysis robust? Soil pH 0.0001 541 2715 7165709 Yes Yes Crop yield < 0.0001 489 2455 762957 Yes Yes CEC c 0.0632 203 1025 1639837 No Yes OM d 0.0236 232 1170 4843590 Yes Yes BS e < 0.0001 54 280 64986 Yes Yes BD f 5 n + 10, the results are regarded as a dependable estimate of the true effect; c cation exchange capacity; d organic matter; e cation saturation; f bulk density. Effect of biochar characteristics on soil pH and crop yield Application of biochar has a positive effect on soil pH and crop yield ( P < 0.001), with an overall increase of 11% and 49%, respectively, compared with a control without biochar application (Fig. 3 ). Soil pH significantly increases by 7% for biochar pH 6.5–7.5, 11% for biochar pH 7.5–9.5, 14% for biochar pH > 9.5, while there is no significant increase with biochar pH 6.5, without a significant increase with biochar at pH 0.05, Fig. 3 B). The response of soil pH and crop yield are biochar-feedstock-type dependent, with a 13% increase for biosolid-derived biochar, a 12% increase for herbaceous-derived biochar and 10% increase for wood-derived biochar in soil pH ( P < 0.05, Fig. 3 A), whereas there is a 49% increase for biosolid-derived biochar, a 57% increase for herbaceous-derived biochar and a 31% increase for wood-derived biochar in crop yield (Fig. 3 B). The soil pH increases by 9.7% and 9.6% for lower (≤ 300°C) and higher (> 500°C) pyrolysis temperature, respectively, while it strongly increases by 16% for medium pyrolysis temperature (300–400°C). Meanwhile, medium pyrolysis temperature (300–400°C) significantly increases crop yield by 71%, and higher (400–500°C, > 500°C) pyrolysis temperature increase crop yield by 38% and 32%, respectively (Fig. 3 B), while biochar produced at lower (≤ 300°C) pyrolysis temperature has no significant impact on crop yield. Soil pH and yield increase significantly in all study setting including pot studies in a greenhouse, incubation experiments in the laboratory and field studies, with the strongest enhancing effect observed under pot conditions ( P < 0.05, Fig. 3 ). Effect of soil properties on soil pH and crop yield Three initial soil properties, including pH, CEC, and OM were selected to explore the effect of soil properties on soil pH and crop yield in response to biochar application (Fig. 4 ). Biochar application to most of the soils with different properties exhibits a consistent increase in soil pH and crop yield ( P < 0.05). Biochar application significantly enhances soil pH across all ranges of initial soil pH, especially in soils with lower initial pH values ( P < 0.05). Upon biochar application to extremely acidic soils with pH 4.5-5.0 and pH 6.0 (Fig. 4 B). Biochar application to soils with relatively high (> 20 cmol kg − 1 ) or low CEC ( 0.05, Fig. 4 A) or crop yield ( P > 0.05, Fig. 4 B). However, soil pH significantly increases by 13–16% ( P < 0.001) at medium CEC ranging from 5 to 20 cmol kg − 1 , and crop yield significantly increases by 60–80% ( P < 0.001), correspondingly (Fig. 4 ). Soil pH and yield is significantly increased at over the entire range of initial soil OM content, especially in soils with an initial OM content less than 6 g kg − 1 where soil pH further increases by 20% ( P < 0.001, Fig. 4 A) and crop yield by 50% ( P < 0.001, Fig. 3 ). Soil property changes in response to biochar application and their correlation with changes in crop yield Biochar application increases soil OM, CEC and CS by 54% ( P < 0.0001), 33% ( P < 0.001) and 43% ( P < 0.0001), respectively, and decreases soil BD by 11% ( P < 0.01), compared with a control without biochar application (Fig. 5 ). In response to biochar application, soil OM significantly increases under pot (by 82%, P < 0.01) and field (by 36%, P 0.05) under laboratory incubation. Similarly, biochar produced from different feedstock significantly increase soil OM compared with the control (Fig. S2). The increase in soil OM is greatest (70%) with the application of herbaceous-derived biochar, while it was 67% and 45% from the biochar derived from wood and biosolid, respectively. Biochar pyrolyzed under > 300℃ can ultimately increase soil OM (65–69%), while there is no significant difference under lower pyrolysis temperature, < 300℃, compared with the control. Soil CEC significantly increased under pot (by 38%, P < 0.001) and field conditions (by 30%, P < 0.05), but incubation condition (Fig. S2B), with more pronounced increases for pot studies. Wood-derived and herbaceous-derived biochar increase soil CEC by 24% ( P < 0.001) and 20% ( P 0.05). Soil CEC has significantly increased, while there is no significant difference in effect size on soil CEC among various biochar application produced at different pyrolysis temperatures. Soil BD significantly decreases under field condition and does not change for pot condition (Fig. S2C). It also decreases by 15% and 14% for wood-derived and herbaceous-derived biochar application, respectively, but not for biosolid-derived biochar. Soil BD significantly decreases after the application of biochar pyrolyzed at a temperature of > 300℃, and shows a most significant decrease (46%) with pyrolysis temperature ranging from 300 to 400℃. Spearman correlations between the response of crop yield and soil properties to the soil biochar application show that the increase in yield is intensely and positively correlated with soil pH ( P < 0.001), OM ( P < 0.001) and CS ( P < 0.001), while there is no significant correlation with CEC and BD (Fig. 6 ). The increase in soil pH is positively correlated with CEC ( P < 0.05), OM ( P < 0.001) and CS ( P < 0.001), while it is negatively correlated with BD ( P < 0.05, Fig. 5 ). Discussion Soil aggregate stability, nutrient availability, metal toxicity, and biological activities are ultimately affected by soil pH, and an appropriate soil pH can maintain better crop productivity (Zhao et al. 2020 ; Goulding 2016 ). Various soil amendments (lime, by-product, manure, straw and biochar) are applied to alleviate soil acidification, among which biochar is regarded as a promising material (Masud et al. 2020 ; Zhang et al. 2023 ). In agreement with previous results (Hailegnaw et al. 2019 ; Rees et al. 2014 ; Zhang et al. 2023 ), our meta-analysis results showed that biochar application significantly increased soil pH (11%) compared with a control without biochar application, and thus alleviated soil acidification (Fig. 3 A). Biochar alleviates soil acidity due to its alkaline nature and high pH-buffering capacity. Carbonates and oxides in biochar are the major components contributing to alkalinity, and functional groups such as –COO − and –O − can also react with H + and thus increase soil pH (Dai et al. 2017 ; Xu et al. 2012 ). Biochar pH is strongly affected by pyrolysis temperature and feedstock type. Pyrolysis temperature strongly influences biochar physicochemical properties (e.g., pH and functional groups) and further affects the effects of biochar as a soil amendment to alleviate soil acidification (Tomczyk et al. 2020 ; Ding et al. 2014 ). Previous research has reported that the average biochar pH is 5.0, when pyrolyzed at 300–399°C, while it is 9.0 when pyrolyzed at 600–699°C. This is consistent with our meta-analysis result showing that the average pH of biochar pyrolyzed at ≤ 300°C is 8.4, and it gradually increases with increasing pyrolysis temperatures (Fig. 7 A). This effect is induced by the breakdown of lignin and other organic molecules with stronger chemical bonds under higher pyrolysis temperatures (Tomczyk et al. 2020 ). According to our results, the greatest soil pH increase occurred at pyrolysis temperatures of 300–400°C, not at > 500°C (Fig. 2 A) which demonstrates that the higher pH of biochar pyrolyzed at higher temperature was not necessarily related to greater acid-neutralizing capacity. Van Zwieten et al. ( 2010a ), for example, found that papermill-residue biochar has a pH of 6.8 with an acid-neutralizing capacity of 18%, while biochar produced from biosolid has a higher pH of 7.9, but a lower neutralizing capacity of 1.7%. Biochar produced from herbaceous material shows a higher pH and acid-neutralizing capacity (Fig. 3 A and 7 B), which can be attributed to the high ash content of non-wood-derived biochar than that of wood-derived biochar (H El-Gamal et al. 2017 ). Biochar application increased crop yield by 49% in acidic soils (Fig. 3 B), and many studies report that the increase in crop yield is related to alleviated Al 3+ toxicity and increased soil nutrient availability (Zhang et al. 2021a ; Zhang et al. 2021b ; Tang et al. 2003 ). The influence of biochar application on crop yield also depends on interactions of pyrolysis temperature and feedstock type. Previous study show that biochar produced at pyrolysis temperature of 600°C) decreases crop yield (Singh et al. 2022 ; Li et al. 2019b ). This is consistent with our meta-analysis results, which demonstrate that biochar produced at pyrolysis temperature of 300–400°C is most effective at increasing crop yield (Fig. 3 B). Biochar produced at lower temperature does not have an adequate specific surface area for adsorption, yet biochar produced at higher temperature may have lost some functional groups for surface cation exchange which decreases the retention of mineral nutrients available for plant growth (Li et al. 2019b ). Therefore, it is essential to choose an optimal pyrolysis temperature for biochar production to match the biochar properties towards a high crop yield. In comparison with wood-derived biochar, herbaceous- and biosolid-derived biochar can further increase crop yield (Fig. 3 B) which may be attributed to the greater amounts of mineral nutrients in herbaceous- and biosolid-derived biochar and higher content of lignin in wood-derived biochar to immobilize mineral nutrients (Latini et al. 2019 ; Kloss et al. 2012 ). Caires et al. ( 2008 ) observed that the response of yield varies among crops due to crop-specific sensitivity to acid soil conditions. Our finding of no difference in the yield of acid-resistant crop (e.g., tea) after biochar application was in agreement with previous research conducted in an acid soil with different soil amendments (Zhang et al. 2023 ), however, a considerably more substantial response to biochar application was noted for maize and wheat (Fig. 8 ). Given the varying degrees of crop acid sensitivity and the potential impact of biochar, it is prudent to prioritise research on the effects of biochar application on cereal crops rather than concentrating solely on acid-resistant crops like tea. The increase in crop yield following biochar application is positively correlated with the increase in soil CEC, OM, CS and the slight decrease in BD (Fig. 6 ). Biochar is a carbon-rich amendment that is also resistant to decay due to the aromatic structure of many molecules it contains, and only approximately 6% of the added biochar is mineralized during the first 8.5 years of incubation (Kuzyakov et al. 2014 ). Tian et al. ( 2016 ) also reported that biochar application increases total soil carbon and particulate organic carbon concentrations in paddy soil. In the present study, OM also responded positively (+ 54%) to biochar application (Fig. 4 ). Our study also quantified the response of soil properties to biochar application (Fig. S2). Pyrolyzed biochar can provide oxygen-containing functional groups, enhancing soil CEC (Uchimiya et al. 2010 ). Biochar contains highly stable forms of carbon, which can result in an increased soil OM. The response of soil pH and crop yield to biochar application is strongly affected by initial soil properties as shown for initial soil CEC, OM, and pH (Fig. 3 ). Although soil pH shows a positive response to biochar application on soils with different acidity, a larger increase is observed on highly acidic soils with pH < 4.5 (Fig. 4 A). This is consistent with previous studies reporting that most of the amendments exhibit alkaline characteristics which can significantly increase the pH of strongly acidic soils with pH values below 5.0 (Li et al. 2019a ; Zhang et al. 2023 ). The yield increase in response to biochar application is less pronounced in soils with high CEC and OM (Fig. 4 B). This is attributed to the impact of a high level of soil CEC and OM affecting both the pH buffer capacity and the pH itself (Najafi and Jalali 2016 ; Xu et al. 2012 ). Conclusion Biochar has long been regarded as a promising amendment to improve soil quality and enhance crop production. This meta-analysis found that biochar application overall increased soil pH by 11% and crop yield by 49%. Biochar pyrolyzed at temperatures between 300–400°C demonstrated the most pronounced impact on soil pH and crop yield, making it the recommended temperature range for biochar preparation. Herbaceous-deriver biochar was the optimal feedstock for soil pH and crop yield. Biochar is most effective in enhancing soil pH and crop yield in strong acidity and low acid-buffering capacity soils. Biochar addition improved soil organic matter, soil CEC, cation saturation, and reduced soil bulk density, contributing to alleviated soil pH and enhanced crop yield. Differences in effect size between incubation, pot and field conditions underscored the importance of carefully controlled environments in field experiments. Long-term field studies are warranted to elucidate the impact of biochar on soil physicochemical properties and crop yield under different environmental conditions, providing crucial insights for optimising biochar application strategies and advancing sustainable agricultural practices. Declarations Acknowledgments This study was financially supported by the National Natural Science Foundation of China (32301699), Key Research and Development Program of Henan Province (231111320300), and Key Scientific Research Project of Universities of Henan Provincial Education Department (24A210017), Major Scientific and Technological Innovation Project of Zhumadian City. We also acknowledge the support from the Chinese Scholarship Council (CSC) and Henan Provincial Education Department providing a postdoc visiting scholarship to Weina Zhang. 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J Environ Qual 41:990-1000 Kochian LV, Pineros MA, Liu J, Magalhaes JV (2015) Plant adaptation to acid soils: The molecular basis for crop aluminum resistance. Annu Rev Plant Biol 66:571-598 Kuzyakov Y, Bogomolova I, Glaser B (2014) Biochar stability in soil: Decomposition during eight years and transformation as assessed by compound-specific 14 C analysis. Soil Biol Biochem 70:229-236 Latini A, Bacci G, Teodoro M, Gattia DM, Bevivino A, Trakal L (2019) The impact of soil-applied biochars from different vegetal feedstocks on durum wheat plant performance and rhizospheric bacterial microbiota in low metal-contaminated soil. Front Microbiol 10:2694 Li GD, Conyers MK, Helyar KR, Lisle CJ, Poile GJ, Cullis BR (2019a) Long-term surface application of lime ameliorates subsurface soil acidity in the mixed farming zone of south-eastern Australia. Geoderma 338:236-246 Li S, Harris S, Anandhi A, Chen G (2019b) Predicting biochar properties and functions based on feedstock and pyrolysis temperature: A review and data syntheses. J Cleaner Prod 215:890-902 Masud MM, Abdulaha-Al Baquy M, Akhter S, Sen R, Barman A, Khatun MR (2020) Liming effects of poultry litter derived biochar on soil acidity amelioration and maize growth. Ecotox Environ Safe 202:110865 Mukherjee A, Zimmerman AR (2013) Organic carbon and nutrient release from a range of laboratory-produced biochars and biochar–soil mixtures. Geoderma 193:122-1302 Najafi S, Jalali M (2016) Effect of heavy metals on pH buffering capacity and solubility of Ca, Mg, K, and P in non-spiked and heavy metal-spiked soils. Environ Monit Assess 188:342 Nguyen DB, Rose MT, Rose TJ, Morris SG, Van Zwieten L (2016) Impact of glyphosate on soil microbial biomass and respiration: A meta-analysis. Soil Biol Biochem 92:50-57 Nguyen TTN, Xu C-Y, Tahmasbian I, Che R, Xu Z, Zhou X, Wallace HM, Bai SH (2017) Effects of biochar on soil available inorganic nitrogen: a review and meta-analysis. Geoderma 288:79-96 Novak, JM, BusscherWJ, Laird DL, Ahmedna M,Watts DW, Niandou MAS (2009) Impact of biochar amendment on fertility of a southeastern coastal plain soil. Soil Sci 174:105-112 Obia A, Mulder J, Martinsen V, Cornelissen G, Børresen T (2016) In situ effects of biochar on aggregation, water retention and porosity in light-textured tropical soils. Soil Till Res 155:35-44 Pariyar P, Kumari K, Jain MK, Jadhao PS (2020) Evaluation of change in biochar properties derived from different feedstock and pyrolysis temperature for environmental and agricultural application. Sci Total Environ 713:136433 Raza S, Miao N, Wang P, Ju X, Chen Z, Zhou J, Kuzyakov Y (2020) Dramatic loss of inorganic carbon by nitrogeno-induced soil acidification in Chinese croplands. Glob Change Biol 26:3738-3751 Rees F, Simonnot MO, Morel JL (2014) Short-term effects of biochar on soil heavy metal mobility are controlled by intra-particle diffusion and soil pH increase. Eur J Soil Sci 65: 149-161 Rothstein HR, Sutton AJ, Borenstein M (2005) Publication bias in meta analysis. Singh H, Northup BK, Rice CW, Prasad PVV (2022) Biochar applications influence soil physical and chemical properties, microbial diversity, and crop productivity: a meta-analysis. Biochar 4:3 Suhadolnik MLS, Costa PS, Castro GM, Lobo FP, Nascimento AM (2021) Comprehensive insights into arsenic-and iron-redox genes, their taxonomy and associated environmental drivers deciphered by a meta-analysis. Environ Int 146:106234 Sun HJ, Lu HY, Chu L, Shao HB, Shi WM (2017) Biochar applied with appropriate rates can reduce N leaching, keep N retention and not increase NH volatilization in a coastal saline soil. Sci Total Environ 575:820-825 Tang C, Rengel Z, Diatloff E, Gazey C (2003) Responses of wheat and barley to liming on a sandy soil with subsoil acidity. Field Crops Res 80:235-244 Tian J, Wang J, Dippold M, Gao Y, Blagodatskaya E, Kuzyakov Y (2016) Biochar affects soil organic matter cycling and microbial functions but does not alter microbial community structure in a paddy soil. Sci Total Environ 556:89-97 Tomczyk A, Sokolowska Z, Boguta P (2020) Biochar physicochemical properties: pyrolysis temperature and feedstock kind effects. Rev Environ Sci Bio 19:191-215 Uchimiya M, Lima IM, Klasson KT, Wartelle LH (2010) Contaminant immobilization and nutrient release by biochar soil amendment: roles of natural organic matter. Chemosphere 80:935-940 Van Zwieten L, Kimber S, Morris S, Chan KY, Downie A, Rust J, Joseph S, Cowie A (2010a) Effects of biochar from slow pyrolysis of papermill waste on agronomic performance and soil fertility. Plant Soil 327:235-246 van Zwieten L, Kimber S, Morris S, Downie A, Berger E, Rust J, Scheer C (2010b) Influence of biochars on flux of N 2 O and CO 2 from Ferrosol. Aust J Soil Res 48:555-568 Wei W, Yang H, Fan M, Chen H, Guo D, Cao J, Kuzyakov Y (2020) Biochar effects on crop yields and nitrogen loss depending on fertilization. Sci Total Environ 702:134423 Xu RK, Zhao AZ, Yuan JH, Jiang J (2012) pH buffering capacity of acid soils from tropical and subtropical regions of China as influenced by incorporation of crop straw biochars. J Soil Sediment 12:494-502 Yadav DS, Jaiswal B, Gautam M, Agrawal M (2020) Soil acidification and its impact on plants. In: Singh P, Singh SK, Prasad SM (eds) Plant Responses to Soil Pollution. Springer Singapore, Singapore, pp 1-26. Yang F, Cao X, Gao B, Zhao L, Li F (2015) Short-term effects of rice straw biochar on sorption, emission, and transformation of soil NH 4 + -N. Environ Sci Pollut Res 22:9184–9192 Yuan C, Gao B, Peng Y, Gao X, Fan B, Chen Q (2021) A meta-analysis of heavy metal bioavailability response to biochar aging: Importance of soil and biochar properties. Sci Total Environ 756:144058 Zhang Q, Zhu J, Wang Q, Xu L, Li M, Dai G, Mulder J, Xi Y, He N (2022) Soil acidification in China's forests due to atmospheric acid deposition from 1980 to 2050. Sci Bull 67:914-917 Zhang S, Yang W, Muneer MA, Ji Z, Tong L, Zhang X, Li X, Wang W, Zhang F, Wu L (2021a) Integrated use of lime with Mg fertilizer significantly improves the pomelo yield, quality, economic returns and soil physicochemical properties under acidic soil of southern China. Sci Hortic 290:110502 Zhang S, Yang X, Hsu L-C, Liu Y-T, Wang S-L, White JR, Shaheen SM, Chen Q, Rinklebe J (2021b) Soil acidification enhances the mobilization of phosphorus under anoxic conditions in an agricultural soil: Investigating the potential for loss of phosphorus to water and the associated environmental risk. Sci Total Environ 793:148531 Zhang S, Zhu Q, de Vries W, Ros GH, Chen X, Muneer MA, Zhang F, Wu L (2023) Effects of soil amendments on soil acidity and crop yields in acidic soils: A world-wide meta-analysis. J Environ Manage 345:118531 Zhang Y, He X, Liang H, Zhao J, Zhang Y, Xu C, Shi X (2016) Long-term tobacco plantation induces soil acidification and soil base cation loss. Environ Sci Pollut Res 23:5442-5450 Zhao WR, Li JY, Deng KY, Shi RY, Jiang J, Hong ZN, Qian W, He X, Xu RK (2020) Effects of crop straw biochars on aluminum species in soil solution as related with the growth and yield of canola ( Brassica napus L.) in an acidic Ultisol under field condition. Environ Sci Pollut Res 27:30178-30189 Zhu Q, Liu X, Hao T, Zeng M, Shen J, Zhang F, De Vries W (2018) Modeling soil acidification in typical Chinese cropping systems. Sci Total Environ 613-614:1339-1348 Supplementary Files Supplementarymaterials202403013.docx Cite Share Download PDF Status: Published Journal Publication published 16 May, 2025 Read the published version in Plant and Soil → Version 1 posted Editorial decision: Major revisions 08 Jul, 2024 Reviewers agreed at journal 21 Mar, 2024 Reviewers invited by journal 20 Mar, 2024 Editor invited by journal 19 Mar, 2024 First submitted to journal 18 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4128294","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":281899068,"identity":"4e962d42-99e7-47f1-8500-66be29ce6f73","order_by":0,"name":"Junhe Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYBACPmYGBgMGhgMM9sebDxz4UEGEFjaYFoYzxxIPzjhDjBYIBdRyI8f4MG8LMVrYeQyKeXfckWOckfPhAG8Dgzy/2AFCDuMxMOY988yYmefthgOSOxgMZ85OIEZL2+HENvbcDQcMzzAkGNwmUkt9D0POgwOJbSRoSZDgyGE4cJA4LWwFhnPbDhtu4DlmcLDhjARhv/DzH95m8LbtsLwBe/Pjz38qbOT5pQloAVlkgMSRIKgcBJgfEKVsFIyCUTAKRi4AAIbiRF8QdMt5AAAAAElFTkSuQmCC","orcid":"","institution":"Huanghuai University","correspondingAuthor":true,"prefix":"","firstName":"Junhe","middleName":"","lastName":"Liu","suffix":""},{"id":281899069,"identity":"c2d77191-6c62-4fec-b8bf-2cd81e660cda","order_by":1,"name":"Weina Zhang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Weina","middleName":"","lastName":"Zhang","suffix":""},{"id":281899070,"identity":"6217a9fd-0448-4b67-bc00-fd07cb9e0287","order_by":2,"name":"Jiayin Pang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jiayin","middleName":"","lastName":"Pang","suffix":""},{"id":281899071,"identity":"88c04897-e460-421d-b576-947a621ea0b2","order_by":3,"name":"Junfeng Qi","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Junfeng","middleName":"","lastName":"Qi","suffix":""},{"id":281899072,"identity":"556987cd-3248-49c8-ab0a-824cc5f18ab3","order_by":4,"name":"Yang Lu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Lu","suffix":""},{"id":281899073,"identity":"431111fe-b995-4a52-a0cd-d3d38b89dba4","order_by":5,"name":"Mingfu Yu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Mingfu","middleName":"","lastName":"Yu","suffix":""},{"id":281899074,"identity":"83736622-3ce6-4600-803c-fdb82c41deaf","order_by":6,"name":"Haigang Li","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Haigang","middleName":"","lastName":"Li","suffix":""},{"id":281899075,"identity":"ee184ffa-4cac-47c0-b4b2-9d76172200b8","order_by":7,"name":"Enli Wang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Enli","middleName":"","lastName":"Wang","suffix":""},{"id":281899076,"identity":"1f815d64-869a-4167-a0db-abbbfb436503","order_by":8,"name":"Hans Lambers","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Hans","middleName":"","lastName":"Lambers","suffix":""}],"badges":[],"createdAt":"2024-03-19 07:46:58","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4128294/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4128294/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11104-025-07490-8","type":"published","date":"2025-05-16T15:58:12+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53420922,"identity":"6599ed88-39d7-498d-9494-ad65d20b5324","added_by":"auto","created_at":"2024-03-25 18:30:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":253093,"visible":true,"origin":"","legend":"\u003cp\u003eSite distribution of experiments (including field and pot, excluding incubation) including 41 sites used in the meta-analysis.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4128294/v1/986e6437aa3e209916bf21c6.png"},{"id":53420920,"identity":"7353330c-892f-48b9-a472-6b1dfe2046a4","added_by":"auto","created_at":"2024-03-25 18:30:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":223446,"visible":true,"origin":"","legend":"\u003cp\u003eThe relative influence (%) of explanatory variables on soil pH (A) and crop yield (B) in response to biochar addition, as determined by Boosted Regression Trees (BRT) analysis. Explanatory variables include biochar characteristics (pyrolysis temperature, feedstock), soil properties (soil CEC, soil OM) and type of study (field, pot, incubation).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4128294/v1/548b7b7d3e22f4bc3cca219f.png"},{"id":53420924,"identity":"585b6598-467f-49b3-adf4-6364710450c2","added_by":"auto","created_at":"2024-03-25 18:30:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":488883,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of biochar properties and type of study on the change of soil pH (A) and crop yield (B). Symbols represent the mean percentage change of effect size with a 95% confidence interval (CI), with effects being significant when the CI does not overlap with the zero line (\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05); red broken lines serve as overall effects and numbers in parentheses indicate the number of observations.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4128294/v1/b434547f388051b51126375e.png"},{"id":53421348,"identity":"369cec56-c1c6-4e30-b7e4-c3b521318d57","added_by":"auto","created_at":"2024-03-25 18:38:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":414192,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of initial soil properties on the change of soil pH (A) and crop yield (B). Symbols represent the mean percentage change of effect size with a 95% confidence interval (CI), with effects being significant when the CI does not overlap with the zero line (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05); red broken lines serve as overall effects and numbers in parentheses indicate the number of observations.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4128294/v1/2eeeb1b20dcdd153c2f2b672.png"},{"id":53420925,"identity":"adb9bd01-c0da-4d6a-85e0-a3db0e28d4ca","added_by":"auto","created_at":"2024-03-25 18:30:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":96753,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage change in soil organic matter (OM), cation exchange capacity (CEC), cation saturation (CS) and bulk density (BD) in response to biochar application. Symbols represent the mean percentage change of effect size with a 95% confidence interval (CI), with effects being significant if the CI does not overlap with the zero line (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05); red broken lines serve as overall effects and numbers in parentheses indicate the number of observations.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4128294/v1/16637ca905feede44289e4d6.png"},{"id":53420927,"identity":"70f54e44-d60b-4e42-bde8-e8842480401d","added_by":"auto","created_at":"2024-03-25 18:30:34","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":274641,"visible":true,"origin":"","legend":"\u003cp\u003eSpearman correlations between the effect size of yield, soil pH, bulk density (BD), cation saturation (CS), organic matter (OM), cation exchange capacity (CEC). The upper right triangle indicates the significance of correlations, denoted as **, *** at\u003cem\u003e P \u003c/em\u003e\u0026lt; 0.05 and \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, respectively. Non-significant correlations are represented by blanks. The lower left triangle displays the correlation coefficient (r). Red and blue indicate positive and negative correlations, respectively.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4128294/v1/af186cac2e5bb87800d0d1af.png"},{"id":53420928,"identity":"9d4a27b0-fb90-4aed-af4b-d113792f4b89","added_by":"auto","created_at":"2024-03-25 18:30:34","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":100589,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of \u003ca href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/pyrolysis\" title=\"Learn more about pyrolysis from ScienceDirect's AI-generated Topic Pages\"\u003epyrolysis\u003c/a\u003e temperature (A) and feedstock type (B) on biochar pH. Different letters indicate a significant (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) difference among groups.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-4128294/v1/50b842f6cf3ca97e7b29adf8.png"},{"id":53420929,"identity":"6177cadf-40f2-46a6-981d-291d71bd2302","added_by":"auto","created_at":"2024-03-25 18:30:34","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":344313,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage change in soil pH (A) and crop yield (B) in response to biochar application in different crops. The dots and error bars represent the mean and 95% confidence intervals (CI) of the effect size, respectively, with effects being significant if the CI does not overlap with the broken red zero line (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). The numbers in parentheses indicate the number of observations.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-4128294/v1/a0c8210c2ae2b85ca759ee89.png"},{"id":83067986,"identity":"569dcabf-4caf-4d1e-b05b-87edddabbe9c","added_by":"auto","created_at":"2025-05-19 16:09:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2864446,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4128294/v1/37d06d06-a40b-4773-bea2-79ed5bf21f00.pdf"},{"id":53420923,"identity":"4495ee36-c2b7-4bea-84ac-5b8602aa31d7","added_by":"auto","created_at":"2024-03-25 18:30:34","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":92501,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials202403013.docx","url":"https://assets-eu.researchsquare.com/files/rs-4128294/v1/6980b681aa021569cf9a6f96.docx"}],"financialInterests":"","formattedTitle":"Biochar's dual impact on soil acidity management and crop yield enhancement: a meta-analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAnthropogenic processes, such as agricultural practices, expedite soil acidification when compared with the natural soil development process (Guo et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Bolan et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Approximately 50% of all global arable land exhibits an acidic profile, and the percentage is gradually increasing due to on-going soil acidification (Kochian et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Soil acidification has obtained significant attention due to its adverse effects on agriculture production and ecosystem services (Guo et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Raza et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Dai et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). It can facilitate the loss of cations (e.g., Na\u003csup\u003e+\u003c/sup\u003e, K\u003csup\u003e+\u003c/sup\u003e, Ca\u003csup\u003e2+\u003c/sup\u003e, Mg\u003csup\u003e2+\u003c/sup\u003e), thus leading to a decline of soil fertility (Zhang et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Acidification can also increase the solubility and mobility of toxic metal (e.g., Cd, Pb), making them more susceptible for crop uptake and increasing their potential to enter the food chain, thereby posing risks to the health of farm animals and humans (Zhu et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Bolan et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, the availability of aluminum (Al) and manganese (Mn) increases in the soil solution at low soil pH, resulting in root damage and decreased crop yield (Yadav et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Those impacts can subsequently threaten food security, underscoring the urgent need to mitigate soil acidification to meet the increasing demand for food (Zhang et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eVarious materials, including agriculture lime, biochar, manure, straw and sludge, are commonly used to relieve soil acidification in agricultural systems (K\u0026auml;tterer et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), among which biochar has been recognized as a promising amendment to overcome soil acidity (Masud et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hass et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Mukherjee and Zimmerman \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Biochar is a carbon-rich solid product produced by pyrolysis of different kinds of biomass under oxygen-limited conditions (Yuan et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Biochar can alleviate soil acidification in a direct way through thereaction of carbonates and oxides in biochar with the H\u003csup\u003e+\u003c/sup\u003e and monomeric Al to decrease soil exchangeable acidity, or in an indirect way by increasing NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N sorption and thus decreasing nitrification rate to prevent H\u003csup\u003e+\u003c/sup\u003e production (Dai et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Novak et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe feedstock types and pyrolysis conditions together determine the biochar physicochemical properties, including pH, cation exchange capacity, and surface area (Pariyar et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mukherjee and Zimmerman \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Thereafter, it can further influence the potential to alleviate soil acidity (Mukherjee and Zimmerman \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Bolan et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Biochar can be produced from a wide range of feedstock, including organic and industrial wastes (e.g., manure, sludge), plant-based materials (e.g., leaves, straw, husks, cobs), and wood-based products (e.g., woodchips, wood pellets) at different pyrolysis temperature under oxygen-limited condition (Farhangi-Abriz et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Singh et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Biochar pH varies from ~\u0026thinsp;3.5 to ~\u0026thinsp;12.2, and a higher pH does not necessarily relate to a greater capacity to increase soil pH. Papermill residue pyrolyzed at 550\u0026deg;C has a pH of 6.8 with an 18% acid-neutralizing capacity that of calcium carbonate, while biosolid-made biochar has a higher pH of 7.9 but with a 1.7% acid neutralizing capacity (van Zwieten et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2010b\u003c/span\u003e). Meanwhile, the pH of green-waste at 350\u0026deg;C and 550\u0026deg;C pyrolysis temperature is 4.9 and 7.3, while the corresponding acid neutralizing capacity is 8.4% and 7.5%, respectively.\u003c/p\u003e \u003cp\u003eBiochar application can ultimately increase crop yield (Arif et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Biederman and Harpole \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) due to increases in soil pH (Sun et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e; Bolan et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), soil carbon storage (Obia et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and water and nutrient retention (Fischer et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bolan et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, it can also cause the decline of crop yield due to nutrient imbalances and enhanced adsorption of NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, increased N immobilization, as well as slower N cycling (Borchard et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Wei et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Bass et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) reported that banana (\u003cem\u003eMusa\u003c/em\u003e sp.) crop yield decreases by 18% with biochar application, with no significant effect on papaya (\u003cem\u003eCarica papaya\u003c/em\u003e) crop yield. Those contradictory results are usually attributed to the heterogeneity of soil type, properties of biochar as a function of feedstock types and pyrolysis conditions and experimental types (laboratory vs. pot vs. field) (Singh et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Dai et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). A general conclusion on the influence of biochar application requires collecting all available data, to analyze the average effect size and the reasons for differences among studies. Meta-analysis is a comprehensive method to investigate studies with inconsistent results and explain differences among studies (Gurevitch et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Thus, this study aim to conduct a meta-analysis to 1) quantify the effects of biochar application on soil pH, crop yield and soil physicochemical properties in acidic soils; 2) establish correlations between crop yield and soil properties.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eLiterature published before July 2023 was collected from Web of Science and China National Knowledge Infrastructure (CNKI) using keywords: 'biochar', 'yield', 'acidic soil' in the topic field. A total of 272 articles were identified and screened based on the following specific criteria for inclusion in the meta-analysis. These criteria included: 1) the presence of a control without biochar application, with all other agronomic practices unchanged; 2) a minimum of three replicates for each treatment; 3) clear reporting of biochar materials and application rates; 4) inclusion of at least one of the following variables impacted by biochar: soil pH, crop yield, cation exchange capacity (CEC), organic matter (OM), bulk density (BD) and cation saturation (CS); 5) initial soil pH should be lower than 6.5, to exclude calcareous soils from the analysis; and 6) reporting of means, standard deviation (SD) or standard error (SE). When SD was unavailable, it was calculated by multiplying SE with the square root of the number of replicates. The GetData Graph Digitizer software was used to extract data from figures where numerical data were not explicitly presented. Finally, 105 peer-reviewed articles with 654 observations from 41 countries or regions were included to elucidate the impacts of biochar on soil pH and crop yield (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The screening process is shown in Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe extracted data were collated as the mean of control and biochar treatment, and corresponding standard deviation and sample size. The biochar characteristics, soil properties, and experimental conditions as provided in each article were also extracted as: 1) biochar characteristics: pH, pyrolysis temperature and feedstock type; 2) soil properties: pH, organic matter (OM), cation exchange capacity (CEC), bulk density (BD) and cation saturation (CS); 2) type of study: field, pot, incubation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData categories\u003c/h2\u003e \u003cp\u003eExplanatory variables including crop, biochar feedstock type, biochar pH, pyrolysis temperature, soil OM, soil CEC, soil BD and soil CS and type of study were selected to explain the response variables (soil pH and crop yield). Each explanatory variable was classified as follows:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eCrop: maize, wheat, rice, legume (soybean, peanut, mung bean), vegetable (tomato, pepper, Chinese cabbage, lettuce, carrot etc.), grass, millet, fruit (citrus, papaya), tea and others;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eBiochar pH (BC pH): (1) BC pH\u0026thinsp;\u0026le;\u0026thinsp;6.5, (2) 6.5\u0026thinsp;\u0026lt;\u0026thinsp;BC pH\u0026thinsp;\u0026le;\u0026thinsp;7.5, (3) 7.5\u0026thinsp;\u0026lt;\u0026thinsp;BC pH\u0026thinsp;\u0026le;\u0026thinsp;9.5, (5) BC pH\u0026thinsp;\u0026gt;\u0026thinsp;9.5, classified following Cayuela et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eBiochar feedstock type: (1) wood (hardwood, bamboo, oak, pine, etc.), (2) herbaceous (wheat straw, maize straw, rice straw, peanut shell, etc.), (3) biosolid (sludge, manure) (Jeffery et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eBiochar pyrolysis temperature (BC PT, ℃): (1) BC PT\u0026thinsp;\u0026le;\u0026thinsp;300, (2) 300\u0026thinsp;\u0026lt;\u0026thinsp;BC PT\u0026thinsp;\u0026le;\u0026thinsp;400, (3) 400\u0026thinsp;\u0026lt;\u0026thinsp;BC PT\u0026thinsp;\u0026le;\u0026thinsp;500, (4) BC PT\u0026thinsp;\u0026gt;\u0026thinsp;500 (Yuan et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInitial soil pH: (1) soil pH\u0026thinsp;\u0026lt;\u0026thinsp;4.5, (2) 4.5\u0026thinsp;\u0026lt;\u0026thinsp;soil pH\u0026thinsp;\u0026lt;\u0026thinsp;5.0, (3) 5.0\u0026thinsp;\u0026lt;\u0026thinsp;soil pH\u0026thinsp;\u0026lt;\u0026thinsp;5.5, (4) 5.5\u0026thinsp;\u0026lt;\u0026thinsp;soil pH\u0026thinsp;\u0026lt;\u0026thinsp;6.0, (5) 6.0\u0026thinsp;\u0026lt;\u0026thinsp;soil pH\u0026thinsp;\u0026lt;\u0026thinsp;6.5 (Zhang et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSoil CEC (cmol kg \u003csup\u003e-1\u003c/sup\u003e): (1) CEC\u0026thinsp;\u0026le;\u0026thinsp;5, (2) 5\u0026thinsp;\u0026lt;\u0026thinsp;CEC\u0026thinsp;\u0026le;\u0026thinsp;10, (3) 10\u0026thinsp;\u0026lt;\u0026thinsp;CEC\u0026thinsp;\u0026le;\u0026thinsp;20, (4) CEC\u0026thinsp;\u0026gt;\u0026thinsp;20;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSoil OM (g kg\u003csup\u003e-1\u003c/sup\u003e): (1) OM\u0026thinsp;\u0026le;\u0026thinsp;6, (2) 6\u0026thinsp;\u0026lt;\u0026thinsp;OM\u0026thinsp;\u0026le;\u0026thinsp;12, (3) 12\u0026thinsp;\u0026lt;\u0026thinsp;OM\u0026thinsp;\u0026le;\u0026thinsp;20, (4) OM\u0026thinsp;\u0026gt;\u0026thinsp;20.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eMeta-analysis\u003c/h2\u003e \u003cp\u003eThe natural log-transformed response ratio (RR) reflects the relative change in one of the response variables due to biochar application, and is calculated based on the ratio of treatment value and control value (Hedges et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1999\u003c/span\u003e):\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\text{ln}RR=\\text{l}\\text{n}\\left(\\frac{Xt}{Xc}\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003eX\u003c/em\u003e\u003csub\u003e\u003cem\u003et\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eX\u003c/em\u003e\u003csub\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sub\u003e represent the values of crop yield, soil pH, OM, CEC, CS and BD in treatment group with biochar application and control group without biochar application, respectively. Effect size was converted to % change according to the following equation (Nguyen et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e):\u003c/p\u003e \u003cp\u003e% change = (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({e}^{\\text{l}\\text{n}\\left(RR\\right)}\\)\u003c/span\u003e\u003c/span\u003e-1) \u0026times; 100\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eA mixed-effects model was selected to calculate effect size and 95% confidence intervals (CIs) for each categorical group using the R package 'metafor'. Significance in difference between biochar application and no biochar application was considered when the CIs did not overlap with zero (Hedges et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Spearman correlations were conducted to examine the correlation between the effect sizes for soil pH, yield, CEC, OM, CS and BD with the cor.test function in R package of 'stats' (Suhadolnik et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Egger\u0026rsquo;s test and Fail-safe number were applied to test the publication bias and robustness of the meta-analysis. The Fail-safe number was calculated and compared with 5n\u0026thinsp;+\u0026thinsp;1 (n is the number of studies) when the Egger\u0026rsquo;s test was significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Rothstein et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA boosted regression tree (BRT) analysis was performed to rank the relative influence of explanatory variables and thus address non-linearity and variable interactions (Elith et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The mixed-effect model combined with BRT has been widely used in a number of meta-analyses (Nguyen et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Nguyen et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Yuan et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). R package 'gbm' was used to conduct the BRT analysis. A Gaussian error structure was used to estimate the optimal number of trees during a 10-fold cross validation, and the model parameters were as follows: tree complexity 5, learning rate 0.005 and bagging fraction 0.75.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGeneral trend\u003c/h2\u003e \u003cp\u003eOur meta-analysis demonstrates that overall, biochar application has a significant impact on soil pH and crop yield. The result of the BRT analysis shows the relative influence of explanatory variables, among which the pyrolysis temperature explains 43% of the change in soil pH, followed by soil CEC (20%), feedstock type (14%), type of study (13%) and soil OM (10%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). For the change in crop yield, pyrolysis temperature explains the majority of the variation (54%), followed by type of study (31%), feedstock type (7%), soil OM (5%) and soil CEC (3%). Between-study heterogeneity was detected in the analyses of this meta-analysis. This was inevitable because the data in this meta-analysis were from a variety of experimental designs, experiment types, biochar characteristics, soil properties and crop types. A significant publication bias was identified (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the meta-analysis, while it did not affect the robustness of the meta-analysis according to the test of Fail-safe number (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) (Nguyen et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Yuan et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTest results of publication bias.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEgger's test\u003c/p\u003e \u003cp\u003e(\u003cem\u003eP\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e \u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003cem\u003en\u003c/em\u003e\u0026thinsp;+\u0026thinsp;10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003efs\u003c/em\u003e\u003c/sub\u003e \u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIs there a bias?\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIs the analysis robust?\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoil pH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7165709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrop yield\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e762957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEC \u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1639837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOM \u003csup\u003e\u003cem\u003ed\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4843590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBS \u003csup\u003e\u003cem\u003ee\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBD \u003csup\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e the number of studies; \u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e Rosenthal\u0026rsquo;s Fail-safe number and if \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003efs\u003c/em\u003e\u003c/sub\u003e \u0026gt; 5\u003cem\u003en\u003c/em\u003e\u0026thinsp;+\u0026thinsp;10, the results are regarded as a dependable estimate of the true effect; \u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e cation exchange capacity; \u003csup\u003e\u003cem\u003ed\u003c/em\u003e\u003c/sup\u003e organic matter; \u003csup\u003e\u003cem\u003ee\u003c/em\u003e\u003c/sup\u003e cation saturation; \u003csup\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sup\u003e bulk density.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eEffect of biochar characteristics on soil pH and crop yield\u003c/h2\u003e \u003cp\u003eApplication of biochar has a positive effect on soil pH and crop yield (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with an overall increase of 11% and 49%, respectively, compared with a control without biochar application (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Soil pH significantly increases by 7% for biochar pH 6.5\u0026ndash;7.5, 11% for biochar pH 7.5\u0026ndash;9.5, 14% for biochar pH\u0026thinsp;\u0026gt;\u0026thinsp;9.5, while there is no significant increase with biochar pH\u0026thinsp;\u0026lt;\u0026thinsp;6.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Correspondingly, the crop yield significantly increases by 40\u0026ndash;60% with biochar pH\u0026thinsp;\u0026gt;\u0026thinsp;6.5, without a significant increase with biochar at pH\u0026thinsp;\u0026lt;\u0026thinsp;6.5 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). The response of soil pH and crop yield are biochar-feedstock-type dependent, with a 13% increase for biosolid-derived biochar, a 12% increase for herbaceous-derived biochar and 10% increase for wood-derived biochar in soil pH (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), whereas there is a 49% increase for biosolid-derived biochar, a 57% increase for herbaceous-derived biochar and a 31% increase for wood-derived biochar in crop yield (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). The soil pH increases by 9.7% and 9.6% for lower (\u0026le;\u0026thinsp;300\u0026deg;C) and higher (\u0026gt;\u0026thinsp;500\u0026deg;C) pyrolysis temperature, respectively, while it strongly increases by 16% for medium pyrolysis temperature (300\u0026ndash;400\u0026deg;C). Meanwhile, medium pyrolysis temperature (300\u0026ndash;400\u0026deg;C) significantly increases crop yield by 71%, and higher (400\u0026ndash;500\u0026deg;C, \u0026gt; 500\u0026deg;C) pyrolysis temperature increase crop yield by 38% and 32%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), while biochar produced at lower (\u0026le;\u0026thinsp;300\u0026deg;C) pyrolysis temperature has no significant impact on crop yield. Soil pH and yield increase significantly in all study setting including pot studies in a greenhouse, incubation experiments in the laboratory and field studies, with the strongest enhancing effect observed under pot conditions (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eEffect of soil properties on soil pH and crop yield\u003c/h2\u003e \u003cp\u003eThree initial soil properties, including pH, CEC, and OM were selected to explore the effect of soil properties on soil pH and crop yield in response to biochar application (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Biochar application to most of the soils with different properties exhibits a consistent increase in soil pH and crop yield (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Biochar application significantly enhances soil pH across all ranges of initial soil pH, especially in soils with lower initial pH values (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Upon biochar application to extremely acidic soils with pH 4.5-5.0 and pH\u0026thinsp;\u0026lt;\u0026thinsp;4.5, soil pH increases by 10% and 13%, respectively and crop yield increases by 53% and 93%, respectively. However, there is no significant increase in crop yield for soil with initial soil pH\u0026thinsp;\u0026gt;\u0026thinsp;6.0 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Biochar application to soils with relatively high (\u0026gt;\u0026thinsp;20 cmol kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) or low CEC (\u0026lt;\u0026thinsp;5 cmol kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) produce no significant effects on soil pH (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA) or crop yield (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). However, soil pH significantly increases by 13\u0026ndash;16% (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) at medium CEC ranging from 5 to 20 cmol kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and crop yield significantly increases by 60\u0026ndash;80% (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), correspondingly (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Soil pH and yield is significantly increased at over the entire range of initial soil OM content, especially in soils with an initial OM content less than 6 g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e where soil pH further increases by 20% (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA) and crop yield by 50% (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eSoil property changes in response to biochar application and their correlation with changes in crop yield\u003c/em\u003e \u003c/p\u003e \u003cp\u003eBiochar application increases soil OM, CEC and CS by 54% (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), 33% (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and 43% (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), respectively, and decreases soil BD by 11% (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), compared with a control without biochar application (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In response to biochar application, soil OM significantly increases under pot (by 82%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and field (by 36%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) conditions (Fig.S2A), but did not increase significantly (by 46%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) under laboratory incubation. Similarly, biochar produced from different feedstock significantly increase soil OM compared with the control (Fig. S2). The increase in soil OM is greatest (70%) with the application of herbaceous-derived biochar, while it was 67% and 45% from the biochar derived from wood and biosolid, respectively. Biochar pyrolyzed under \u0026gt;\u0026thinsp;300℃ can ultimately increase soil OM (65\u0026ndash;69%), while there is no significant difference under lower pyrolysis temperature, \u0026lt; 300℃, compared with the control. Soil CEC significantly increased under pot (by 38%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and field conditions (by 30%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but incubation condition (Fig. S2B), with more pronounced increases for pot studies. Wood-derived and herbaceous-derived biochar increase soil CEC by 24% (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and 20% (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while biosolid-derived biochar does not significantly increase soil CEC (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Soil CEC has significantly increased, while there is no significant difference in effect size on soil CEC among various biochar application produced at different pyrolysis temperatures. Soil BD significantly decreases under field condition and does not change for pot condition (Fig. S2C). It also decreases by 15% and 14% for wood-derived and herbaceous-derived biochar application, respectively, but not for biosolid-derived biochar. Soil BD significantly decreases after the application of biochar pyrolyzed at a temperature of \u0026gt;\u0026thinsp;300℃, and shows a most significant decrease (46%) with pyrolysis temperature ranging from 300 to 400℃.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSpearman correlations between the response of crop yield and soil properties to the soil biochar application show that the increase in yield is intensely and positively correlated with soil pH (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), OM (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and CS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while there is no significant correlation with CEC and BD (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The increase in soil pH is positively correlated with CEC (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), OM (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and CS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while it is negatively correlated with BD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eSoil aggregate stability, nutrient availability, metal toxicity, and biological activities are ultimately affected by soil pH, and an appropriate soil pH can maintain better crop productivity (Zhao et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Goulding \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Various soil amendments (lime, by-product, manure, straw and biochar) are applied to alleviate soil acidification, among which biochar is regarded as a promising material (Masud et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In agreement with previous results (Hailegnaw et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Rees et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), our meta-analysis results showed that biochar application significantly increased soil pH (11%) compared with a control without biochar application, and thus alleviated soil acidification (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Biochar alleviates soil acidity due to its alkaline nature and high pH-buffering capacity. Carbonates and oxides in biochar are the major components contributing to alkalinity, and functional groups such as \u0026ndash;COO\u003csup\u003e\u0026minus;\u003c/sup\u003e and \u0026ndash;O\u003csup\u003e\u0026minus;\u003c/sup\u003e can also react with H\u003csup\u003e+\u003c/sup\u003e and thus increase soil pH (Dai et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Xu et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBiochar pH is strongly affected by pyrolysis temperature and feedstock type. Pyrolysis temperature strongly influences biochar physicochemical properties (e.g., pH and functional groups) and further affects the effects of biochar as a soil amendment to alleviate soil acidification (Tomczyk et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ding et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Previous research has reported that the average biochar pH is 5.0, when pyrolyzed at 300\u0026ndash;399\u0026deg;C, while it is 9.0 when pyrolyzed at 600\u0026ndash;699\u0026deg;C. This is consistent with our meta-analysis result showing that the average pH of biochar pyrolyzed at \u0026le;\u0026thinsp;300\u0026deg;C is 8.4, and it gradually increases with increasing pyrolysis temperatures (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). This effect is induced by the breakdown of lignin and other organic molecules with stronger chemical bonds under higher pyrolysis temperatures (Tomczyk et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). According to our results, the greatest soil pH increase occurred at pyrolysis temperatures of 300\u0026ndash;400\u0026deg;C, not at \u0026gt;\u0026thinsp;500\u0026deg;C (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) which demonstrates that the higher pH of biochar pyrolyzed at higher temperature was not necessarily related to greater acid-neutralizing capacity. Van Zwieten et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2010a\u003c/span\u003e), for example, found that papermill-residue biochar has a pH of 6.8 with an acid-neutralizing capacity of 18%, while biochar produced from biosolid has a higher pH of 7.9, but a lower neutralizing capacity of 1.7%. Biochar produced from herbaceous material shows a higher pH and acid-neutralizing capacity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB), which can be attributed to the high ash content of non-wood-derived biochar than that of wood-derived biochar (H El-Gamal et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBiochar application increased crop yield by 49% in acidic soils (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), and many studies report that the increase in crop yield is related to alleviated Al\u003csup\u003e3+\u003c/sup\u003e toxicity and increased soil nutrient availability (Zhang et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e; Tang et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The influence of biochar application on crop yield also depends on interactions of pyrolysis temperature and feedstock type. Previous study show that biochar produced at pyrolysis temperature of \u0026lt;\u0026thinsp;500\u0026deg;C is most effective in stimulating crop yield, while biochar produced under higher temperature (\u0026gt;\u0026thinsp;600\u0026deg;C) decreases crop yield (Singh et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e). This is consistent with our meta-analysis results, which demonstrate that biochar produced at pyrolysis temperature of 300\u0026ndash;400\u0026deg;C is most effective at increasing crop yield (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Biochar produced at lower temperature does not have an adequate specific surface area for adsorption, yet biochar produced at higher temperature may have lost some functional groups for surface cation exchange which decreases the retention of mineral nutrients available for plant growth (Li et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e). Therefore, it is essential to choose an optimal pyrolysis temperature for biochar production to match the biochar properties towards a high crop yield. In comparison with wood-derived biochar, herbaceous- and biosolid-derived biochar can further increase crop yield (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) which may be attributed to the greater amounts of mineral nutrients in herbaceous- and biosolid-derived biochar and higher content of lignin in wood-derived biochar to immobilize mineral nutrients (Latini et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kloss et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Caires et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) observed that the response of yield varies among crops due to crop-specific sensitivity to acid soil conditions. Our finding of no difference in the yield of acid-resistant crop (e.g., tea) after biochar application was in agreement with previous research conducted in an acid soil with different soil amendments (Zhang et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), however, a considerably more substantial response to biochar application was noted for maize and wheat (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Given the varying degrees of crop acid sensitivity and the potential impact of biochar, it is prudent to prioritise research on the effects of biochar application on cereal crops rather than concentrating solely on acid-resistant crops like tea.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe increase in crop yield following biochar application is positively correlated with the increase in soil CEC, OM, CS and the slight decrease in BD (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Biochar is a carbon-rich amendment that is also resistant to decay due to the aromatic structure of many molecules it contains, and only approximately 6% of the added biochar is mineralized during the first 8.5 years of incubation (Kuzyakov et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Tian et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) also reported that biochar application increases total soil carbon and particulate organic carbon concentrations in paddy soil. In the present study, OM also responded positively (+\u0026thinsp;54%) to biochar application (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Our study also quantified the response of soil properties to biochar application (Fig. S2). Pyrolyzed biochar can provide oxygen-containing functional groups, enhancing soil CEC (Uchimiya et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Biochar contains highly stable forms of carbon, which can result in an increased soil OM. The response of soil pH and crop yield to biochar application is strongly affected by initial soil properties as shown for initial soil CEC, OM, and pH (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Although soil pH shows a positive response to biochar application on soils with different acidity, a larger increase is observed on highly acidic soils with pH\u0026thinsp;\u0026lt;\u0026thinsp;4.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). This is consistent with previous studies reporting that most of the amendments exhibit alkaline characteristics which can significantly increase the pH of strongly acidic soils with pH values below 5.0 (Li et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The yield increase in response to biochar application is less pronounced in soils with high CEC and OM (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). This is attributed to the impact of a high level of soil CEC and OM affecting both the pH buffer capacity and the pH itself (Najafi and Jalali \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Xu et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eBiochar has long been regarded as a promising amendment to improve soil quality and enhance crop production. This meta-analysis found that biochar application overall increased soil pH by 11% and crop yield by 49%. Biochar pyrolyzed at temperatures between 300\u0026ndash;400\u0026deg;C demonstrated the most pronounced impact on soil pH and crop yield, making it the recommended temperature range for biochar preparation. Herbaceous-deriver biochar was the optimal feedstock for soil pH and crop yield. Biochar is most effective in enhancing soil pH and crop yield in strong acidity and low acid-buffering capacity soils. Biochar addition improved soil organic matter, soil CEC, cation saturation, and reduced soil bulk density, contributing to alleviated soil pH and enhanced crop yield. Differences in effect size between incubation, pot and field conditions underscored the importance of carefully controlled environments in field experiments. Long-term field studies are warranted to elucidate the impact of biochar on soil physicochemical properties and crop yield under different environmental conditions, providing crucial insights for optimising biochar application strategies and advancing sustainable agricultural practices.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was financially supported by the National Natural Science Foundation of China (32301699), Key Research and Development Program of Henan Province (231111320300), and Key Scientific Research Project of Universities of Henan Provincial Education Department (24A210017), Major Scientific and Technological Innovation\u0026nbsp;Project of Zhumadian City. We also acknowledge the support from the Chinese Scholarship Council (CSC) and Henan Provincial Education Department providing a postdoc visiting scholarship to Weina Zhang. Hans Lambers was supported by funding from the Deputy Vice Chancellor (Research) at the University of Western\u003c/p\u003e\n\u003cp\u003eAustralia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArif M, Ilyas M, Riaz M, Ali K, Shan K, Haq IU, Fahad S (2017) Biochar improves phosphorus use efficiency of organic-inorganic fertilizers, maize-wheat productivity and soil quality in a low fertility alkaline soil. Field Crops Res 214:25-37\u003c/li\u003e\n\u003cli\u003eBass AM, Bird MI, Kay G, Muirhead B (2016) Soil properties, greenhouse gas emissions and crop yield under compost, biochar and co-composted biochar in two tropical agronomic systems. 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J Environ Manage 345:118531\u003c/li\u003e\n\u003cli\u003eZhang Y, He X, Liang H, Zhao J, Zhang Y, Xu C, Shi X (2016) Long-term tobacco plantation induces soil acidification and soil base cation loss. Environ Sci Pollut Res 23:5442-5450\u003c/li\u003e\n\u003cli\u003eZhao WR, Li JY, Deng KY, Shi RY, Jiang J, Hong ZN, Qian W, He X, Xu RK (2020) Effects of crop straw biochars on aluminum species in soil solution as related with the growth and yield of canola (\u003cem\u003eBrassica napus \u003c/em\u003eL.) in an acidic Ultisol under field condition. Environ Sci Pollut Res 27:30178-30189\u003c/li\u003e\n\u003cli\u003eZhu Q, Liu X, Hao T, Zeng M, Shen J, Zhang F, De Vries W (2018) Modeling soil acidification in typical Chinese cropping systems. Sci Total Environ 613-614:1339-1348 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Biochar, Crop yield, Meta-analysis, Soil acidification, Soil properties","lastPublishedDoi":"10.21203/rs.3.rs-4128294/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4128294/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground and Aims\u003c/h2\u003e \u003cp\u003eBiochar is a promising and widely used soil amendment to alleviate soil acidification and improve crop productivity. Quantitative analysis of the impact of biochar application on soil pH and crop yield can help promote its optimal utilization.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe compiled 654 observations from 105 peer-reviewed articles to investigate the impact of biochar application on crop yield, soil pH and other physicochemical properties in acidic soils.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eApplication of biochar significantly increased soil pH and crop yield by 11% and 49%, respectively. The increase in soil pH exhibited a positive correlation with crop yield, and the relationship varied among crop type. The most significant increase in soil pH and crop yield following biochar application was observed in strongly acidic soils (pH\u0026thinsp;\u0026lt;\u0026thinsp;4.5) characterized by low cation exchange capacity, ranging from 5 to 10 cmol kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and low soil organic matter content, \u0026lt; 6 g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Among soil physicochemical properties, biochar application increased soil organic matter, cation exchange capacity, and cation saturation by 54%, 33% and 43%, respectively, while reduced soil bulk density by 11%. Biochar derived from herbaceous sources and pyrolyzed at an optimal temperature of 300\u0026ndash;400\u0026deg;C had a significant and positive affect on soil pH (+\u0026thinsp;16%) and crop yield (+\u0026thinsp;71%).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur findings can aid in optimizing management strategies for biochar application on acidic soils, whereas more long-term field experiments should be conducted to help provide better explanations for changes in biochar properties as it ages.\u003c/p\u003e","manuscriptTitle":"Biochar's dual impact on soil acidity management and crop yield enhancement: a meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-25 18:30:27","doi":"10.21203/rs.3.rs-4128294/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2024-07-08T06:31:52+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-03-21T17:12:16+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-20T15:30:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Plant and Soil","date":"2024-03-20T02:15:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant and Soil","date":"2024-03-19T03:46:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"fd8c6210-fe3d-4dce-9fd0-a028afd7daae","owner":[],"postedDate":"March 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-19T16:05:15+00:00","versionOfRecord":{"articleIdentity":"rs-4128294","link":"https://doi.org/10.1007/s11104-025-07490-8","journal":{"identity":"plant-and-soil","isVorOnly":false,"title":"Plant and Soil"},"publishedOn":"2025-05-16 15:58:12","publishedOnDateReadable":"May 16th, 2025"},"versionCreatedAt":"2024-03-25 18:30:27","video":"","vorDoi":"10.1007/s11104-025-07490-8","vorDoiUrl":"https://doi.org/10.1007/s11104-025-07490-8","workflowStages":[]},"version":"v1","identity":"rs-4128294","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4128294","identity":"rs-4128294","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}